Our results suggest that imbalance in the meta-dataset has minimal effect on the meta-learning procedure. This could result from standard episodic meta-training that samples classes with equal probability and causes natural re-sampling. Likely, datasets with lower intra-class variation and larger imbalance [1]}, [2]}, [3]} could produce more dramatic performance changes.
